AHA Annual Survey Database for Fiscal Year 2020 is a comprehensive hospital database for health services research and market analysis. It is derived primarily from the AHA Annual Survey of Hospitals, which has been conducted by the American Hospital Association (AHA) or its subsidiary, Health Forum, since 1946. The survey responses are supplemented by data drawn from the American Hospital Association registration database, the US Census Bureau, hospital accrediting bodies, and other organizations. The database maintains hospital characteristics across time to allow researchers to conduct time-series analyses.

AHA Annual Survey Database™ for Fiscal Year 2022 is a comprehensive hospital database for peer comparisons, market analysis, and health services research. It is produced primarily from the AHA Annual Survey of Hospitals, which has been administered by the American Hospital Association (AHA) since 1946. The survey responses are supplemented by data drawn the U.S. Census Bureau, hospital accrediting bodies, and other organizations.

From the Web site: The American Hospital Directory® provides data, statistics, and analytics about more than 7,000 hospitals nationwide. AHD.com® hospital information includes both public and private sources such as Medicare claims data, hospital cost reports, and commercial licensors. AHD® is not affiliated with the American Hospital Association (AHA) and is not a source for AHA Data. Our data are evidence-based and derived from the most definitive sources.

Hospital characteristics by EHR status.

Regression results of patient experience measures.

Data on community hospital beds in the United States, by state. Data are from Health, United States. SOURCE: American Hospital Association (AHA) Annual Survey of Hospitals, Hospital Statistics. Search, visualize, and download these and other estimates from a wide range of health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

Data addressing the financial impact of site-neutral payment reforms on rural hospitals.

Data on hospital admission, average length of stay, outpatient visits, and outpatient surgery in the United States, by type of ownership and size of hospital. Data are from Health, United States. SOURCE: American Hospital Association (AHA) Annual Survey of Hospitals, Hospital Statistics. Search, visualize, and download these and other estimates from a wide range of health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

This hospitals GIS data represents the locations and selected attributes for hospitals included in the FY2005 edition of the American Hospital Association (AHA) Annual Survey Database and located in Vermont or within 25 miles of Vermont in Massachusetts, New Hampshire, or New York. Data fields detail hospital names, services, admissions, visits, beds, Medicare, health, society, structure, and location. Fields were added by the Vermont Dept. of Health (VDH) detailing hospital type and primary phone number. July 2021: Added webite hyperlinks and changed projection to WGS_1984_Web_Mercator_Auxiliary_Sphere for feeding into web maps.

A dataset of hospital bed capacity data for each of 306 U.S. hospital markets, including data for nine different models of COVID-19 infection scenarios. The data comes from a team of researchers at the Harvard Global Data Institute. They modeled various scenarios, in which 20%, 40% and 60% of the adult population would be infected with the novel coronavirus, many of whom would have no or few symptoms, and examined whether hospitals had the capacity to handle them if the cases came in over six months, 12 months and 18 months. Hospital bed figures were derived from recent surveys conducted by the American Hospital Association and data compiled by the American Hospital Directory. The data is divided into slightly more than 300 regions, also known as hospital referral regions.

The Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) are a set of hospital databases that contain the universe of hospital inpatient discharge abstracts from data organizations in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SID are based on data from short term, acute care, nonfederal hospitals. Some States include discharges from specialty facilities, such as acute psychiatric hospitals. The SID include all patients, regardless of payer and contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. The SID contain clinical and resource-use information that is included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. In addition to the core set of uniform data elements common to all SID, some include State-specific data elements. The SID exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and county-level data from the Bureau of Health Professions' Area Resource File except in States that do not allow the release of hospital identifiers. Restricted access data files are available with a data use agreement and brief online security training.

The Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) contain the universe of emergency department visits in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SEDD consist of data from hospital-based emergency department visits that do not result in an admission. The SEDD include all patients, regardless of the expected payer including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels.

The SEDD contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and facilities (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., sex, age, race), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. In addition to the core set of uniform data elements common to all SEDD, some include State-specific data elements. The SEDD exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and the Bureau of Health Professions' Area Resource File except in States that do not allow the release of hospital identifiers.

Restricted access data files are available with a data use agreement and brief online security training.

The graph shows the citations of ^'s papers published in each year.

Characteristics of 340 US hospitals grouped by the proportion of private patient rooms (PPRs), based on discharges between September 2015 and August 2016.

Content

Kaiser Health News evaluated the capacity of intensive care unit (ICU) beds around the nation by first identifying the number of ICU beds each hospital reported in its most recent financial cost report, filed annually to the Centers for Medicare & Medicaid Services. KHN included beds reported in the categories of intensive care unit, surgical intensive care unit, coronary care unit and burn intensive care unit.

KHN then totaled the ICU beds per county and matched the data with county population figures from the Census Bureau’s American Community Survey. KHN focused on the number of people 60 and older in each county because older people are considered the most likely group to require hospitalization, given their increased frailty and existing health conditions compared with younger people. For each county, KHN calculated the number of people 60 and older for each ICU bed. KHN also calculated the percentage of county population who were 60 or older.

KHN’s ICU bed tally does not include Veterans Affairs hospitals, which are sure to play a role in treating coronavirus victims, because VA hospitals do not file cost reports. The total number of the nation’s ICU beds in the cost reports is less than the number identified by the American Hospital Association’s annual survey of hospital beds, which is the other authoritative resource on hospital characteristics. Experts attributed the discrepancies to different definitions of what qualifies as an ICU bed and other factors, and told KHN both sources were equally credible.

Acknowledgements

Kaiser Health News

https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/ https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

Fred Schulte: fschulte@kff.org, @fredschulte

Elizabeth Lucas: elucas@kff.org, @eklucas

Jordan Rau: jrau@kff.org, @JordanRau

Liz Szabo: lszabo@kff.org, @LizSzabo

Jay Hancock: jhancock@kff.org, @JayHancock1

Inspiration

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United States Freestanding Emergency Department Market size was valued at USD 7.2 Billion in 2024 and is projected to reach USD 12.9 Billion by 2032, growing at a CAGR of 7.5% from 2026 to 2032. Key Market Drivers:Access to Emergency Care in Underserved Areas: Improved access to emergency care in underserved areas drives growth by meeting critical healthcare needs and reducing hospital overcrowding. In accordance to the American Hospital Association (AHA), around 136 rural hospitals closed between 2010 and 2023, leaving over 20 million Americans with limited access to emergency care. Based on data from the Centers for Medicare and Medicaid Services (CMS), FEDs have reduced average emergency care travel time by 45% in previously underserved communities.Emergency Department Overcrowding Relief: Increasing demand for timely care, limited hospital capacity, and growing patient volumes drive the need for alternative emergency care facilities. The Agency for Healthcare Research and Quality (AHRQ) found that ED wait times increasing by 32% nationwide between 2019 and 2023. According to the 2024 Emergency Care Environment Report by the American College of Emergency Physicians, communities with established FEDs reported a 24% reduction in main hospital ED volumes and a 37% decrease in non-critical wait times.Cost-Effective Care Delivery Model: Cost-effective care delivery models reduce patient expenses, improve access to emergency services, and enhance operational efficiency, driving increased healthcare utilization. In accordance to the Healthcare Financial Management Association, FEDs have 67% lower overhead costs than hospital-based EDs while providing comparable clinical outcomes. The Medicare Payment Advisory Commission data, treatment for common emergency conditions at FEDs is 22-35% less expensive than in hospital-based emergency departments.

The State Emergency Department Databases (SEDD) contain the universe of emergency department visits in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SEDD consist of data from hospital-based emergency departments and include all patients, regardless of payer, e.g., persons covered by Medicare, Medicaid, private insurance, and the uninsured. The SEDD contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and facilities (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., gender, age), total charges, length of stay, and expected payment source (e.g., Medicare, Medicaid, private insurance, self-pay; for some States, additional discrete payer categories, such as managed care). In addition to the core set of uniform data elements common to all SEDD, some include State-specific data elements, such as the patient's race. The SEDD exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and the Area Resource File.

Financial overview and grant giving statistics of Federation Of American Hospitals Inc

The State Ambulatory Surgery Databases (SASD) contain the universe of hospital-based ambulatory surgery encounters in participating States. Some States include ambulatory surgery encounters from free-standing facilities as well. Restricted access data files are available with a data use agreement and brief online security training.

The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SASD include all patients in participating settings, regardless of payer, e.g., persons covered by Medicare, Medicaid, private insurance, and the uninsured.

The SASD contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and facilities (as required by data sources).

Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., gender, age), total charges, and expected payment source (e.g., Medicare, Medicaid, private insurance, self-pay; for some States, additional discrete payer categories, such as managed care). In addition to the core set of uniform data elements common to all SASD, some include State-specific data elements, such as the patient's race. The SASD exclude data elements that could directly or indirectly identify individuals.

For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and the Area Resource File.

Overview The Dartmouth Institute for Health Policy and Clinical Practice (TDI) has created a publicly available source of data that provides researchers, payers, regulators, and innovators with metrics that quantify temporal and regional patterns of health care spending and utilization in the United States. Using CMS Medicare claims data (mostly for age >64 enrollees), Atlas researchers built cohorts (“denominators”) and numerous measures or events (“numerators”) which were then used to calculate rates either by geography or for patients assigned to specific hospitals. These rates, which are calculated consistently across time and place, provide researchers with opportunities to evaluate spatial and temporal variation/trends. In addition to developing rates using Medicare claims data, Atlas researchers developed a variety of measures of hospital and physician capacity by geography using data from the American Hospital Association, the CMS Provider of Services files, CMS Cost Reports, the American Medical Association, and the American Osteopathic Association. This entry contains Dartmouth Atlas rates for these capacity measures, all of which use the number of residents of the geographic area as the denominator. Examples include acute care hospital beds, hospital-based registered nurses, hospital-based employees, physicians, primary care physicians, cardiologists, anesthesiologists, pediatricians, and radiologists. Rates are provided at the hospital referral region (HRR) and hospital service area (HSA) levels, and all rates have been adjusted for age and sex. In contrast to other Atlas rates, these capacity measures were not generated every year; hospital capacity measures are available for 1996, 2006, and 2012, while physician capacity measures are available for 1996, 2006, and 2011. Users downloading data should review the methods sections of the related publications for context as well as for information about any temporal changes in methods. All reports in the Dartmouth Atlas of Health Care series are available from the National Library of Medicine https://www.ncbi.nlm.nih.gov/books/NBK584737/ Note that for the general Dartmouth Atlas rate datasets, which span multiple decades, the author list includes all Dartmouth staff (programmers, analysts, supervisors, etc.) involved in generating all types of Atlas rates across all years. We do not attempt to assign individuals to specific datasets or years.